As a rapidly growing and successful company, ContactEngine positively affects millions of customers’ lives by handling and understanding enormous amounts of data to engage customers in conversations that, over time, build human-computer rapport with each one. As our CEO Prof. Mark K. Smith states in this video, human-computer rapport focuses on using longitudinal data to enhance context when responding to the user during a live conversation.
Applying longitudinal data requires building insight from customer responses and other data sources over prolonged periods. Longitudinal data analysis offers numerous benefits, including identifying and relating events to specific exposures, following change over time in particular individuals, and establishing a sequence of events. Knowing this, we have a moral responsibility to use that data ethically to serve our customers for their betterment.
Artificial Intelligence (AI) and Longitudinal Data
AI is defined as a collection of technologies that excel at extracting insights and patterns from large sets of data, then making predictions based on that information. Today, it helps us get more value out of the data we already have to make predictions about customer behavior. Artificial intelligence is best at finding insights and patterns in large datasets that humans can't see at scale and speed. Further, AI-powered systems can analyze data from hundreds of sources and offer predictions about what works and what doesn't. In turn, data analytics is becoming less labor-intensive, where AI is making almost instantaneous decisions.
The Dark Side of Data (Mis)Use
The popular Netflix documentary, Social Dilemma, investigates the impact companies like Google, Facebook, Twitter and Instagram have on the public. The movie interviews employees as they explain how their companies developed technology that appeared to be useful, but financial pressures to monetize the tools resulted in unethical behavior. The dangerous, arguably unethical part is that these platforms continue to harvest personal data, sell it to advertisers, and target users with ads in a mostly unregulated landscape.
Responsible AI is the answer to at least some of these platform’s problems. Accenture defines responsible AI as focusing on ensuring the ethical, transparent and accountable use of AI technologies consistent with user expectations and organizational values. Alongside these ethical frameworks, there is a need for humans. Without human involvement, these companies could face damage to their brands and loss of consumer trust.
How ContactEngine Safeguards for Ethical Use of Data
So how does ContactEngine measure up? Leading companies use ContactEngine for proactive conversations with their customers to improve CX and to drive down costs, and as such, a large amount of data is collected in this pursuit. This longitudinal data and application to AI to create a perfect customer journey is done in a very pro-customer, ethical manner as explained below.
The ContactEngine AI Board oversees AI development, which includes ensuring our development abides by ContactEngine principles of AI. Further, ContactEngine owns its AI, meaning it does not back off to third-party services. This allows for far greater understanding of how ContactEngine AI makes decisions, and therefore a far greater ability to explain its outputs.
The ContactEngine principles of AI are:
Must benefit each of ContactEngine, our clients, and their customers
We do not compromise our ethics, and everything we do must pass the ‘red face’ test
We need to be able to explain what our AI is doing, or has done, but not necessarily how
We only apply AI where it is relevant to do so, avoiding unnecessary over-complications
Data security is vital, with privacy and confidentiality protected at all times
In the future, ContactEngine may use anticipatory design that allows technology to predict the most useful interaction, help make a decision for the user, and further simplify the experience. Currently, ContactEngine uses omnichannel customer engagement (SMS, email, voice call) but the future could see an extension to more complex channels such as a visual bot, meaning the computer, using longitudinal data, will track facial reactions to detect sentiment. Fully understanding the vast opportunity for and interpretation of longitudinal data makes the importance of responsible and ethical use even more critical.